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1 – 10 of over 4000Raghavendra Rao N.S. and Chitra A.
The purpose of this study is to propose an extended reliability method for an industrial motor drive by integrating the physics of failure (PoF).
Abstract
Purpose
The purpose of this study is to propose an extended reliability method for an industrial motor drive by integrating the physics of failure (PoF).
Design/methodology/approach
Industrial motor drive systems (IMDS) are currently expected to perform beyond the desired operating conditions to meet the demand. The PoF of the subsystem affects its reliability under such harsh operating circumstances. It is crucial to estimate reliability by integrating PoF, which helps in understanding its impact and to develop a fault-tolerant design, particularly in such an integrated drive system. An integrated PoF extended reliability method for industrial drive system is proposed to address this issue. In research, the numerical failure rate of each component of industrial drive is obtained first with the help of the MIL-HDBK-217 military handbook. Furthermore, the mathematically deduced proposed approach is modeled in the GoldSim Monte Carlo reliability workbench.
Findings
From the results, for a 15% rise in integrated PoF, the reliability and availability of the entire IMDS dropped by 23%, resulting in an impact on mean time to failure (MTTF).
Originality/value
The integrated PoF of the motor and motor controller affects industrial drive reliability, which falls to 0.18 with the least MTTF (2.27 years); whose overall reliability of industrial drive drops to 0.06 if it is additionally integrated with communication protocol.
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Velmurugan Kumaresan, S. Saravanasankar and Gianpaolo Di Bona
Through the use of the Markov Decision Model (MDM) approach, this study uncovers significant variations in the availability of machines in both faulty and ideal situations in…
Abstract
Purpose
Through the use of the Markov Decision Model (MDM) approach, this study uncovers significant variations in the availability of machines in both faulty and ideal situations in small and medium-sized enterprises (SMEs). The first-order differential equations are used to construct the mathematical equations from the transition-state diagrams of the separate subsystems in the critical part manufacturing plant.
Design/methodology/approach
To obtain the lowest investment cost, one of the non-traditional optimization strategies is employed in maintenance operations in SMEs in this research. It will use the particle swarm optimization (PSO) algorithm to optimize machine maintenance parameters and find the best solutions, thereby introducing the best decision-making process for optimal maintenance and service operations.
Findings
The major goal of this study is to identify critical subsystems in manufacturing plants and to use an optimal decision-making process to adopt the best maintenance management system in the industry. The optimal findings of this proposed method demonstrate that in problematic conditions, the availability of SME machines can be enhanced by up to 73.25%, while in an ideal situation, the system's availability can be increased by up to 76.17%.
Originality/value
The proposed new optimal decision-support system for this preventive maintenance management in SMEs is based on these findings, and it aims to achieve maximum productivity with the least amount of expenditure in maintenance and service through an optimal planning and scheduling process.
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Nehal Elshaboury, Tarek Zayed and Eslam Mohammed Abdelkader
Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective…
Abstract
Purpose
Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.
Design/methodology/approach
As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.
Findings
Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.
Originality/value
It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.
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Zabih Ghelichi, Monica Gentili and Pitu Mirchandani
This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to…
Abstract
Purpose
This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.
Design/methodology/approach
This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.
Findings
An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.
Originality/value
The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.
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Ahmed M. Attia, Ahmad O. Alatwi, Ahmad Al Hanbali and Omar G. Alsawafy
This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.
Abstract
Purpose
This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.
Design/methodology/approach
A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.
Findings
It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.
Research limitations/implications
The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.
Practical implications
Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.
Originality/value
This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.
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Hafeeza Mamoojee-Khatib, Jiju Antony, Viraiyan Teeroovengadum, Jose Arturo Garza-Reyes, Guilherme Luz Tortorella, Monika Foster and Elizabeth A. Cudney
The purpose of this study is to carry out a comprehensive systematic review of lean implementation frameworks and roadmaps developed over the past decade and report the key…
Abstract
Purpose
The purpose of this study is to carry out a comprehensive systematic review of lean implementation frameworks and roadmaps developed over the past decade and report the key findings along with the limitations and the way forward.
Design/methodology/approach
A systematic review methodology proposed by Tranfield (2003), was followed to identify the relevant works on the research topic. Articles were searched using a set of inclusion criteria in various databases including Google Scholar, Web of Science and Science Direct over a period of 30 years.
Findings
The high failure rate of lean system implementation, reaching a range between 70 and 90% in almost all industries, is a matter of concern. This failure rate is still high even though numerous frameworks and roadmap models exist to streamline lean implementation. There is no standard framework or roadmap identified in the literature and many organisations are implementing lean in their unique ways. However, it would be desirable to develop a practical and systematic roadmap on lean-looking into the cultural and leadership dimensions rather than focusing on a set of tools. Moreover, most frameworks and roadmaps lack the sustenance aspects of lean implementation.
Research limitations/implications
This research only identifies the fundamental gaps with the existing frameworks and roadmaps on lean implementation. The next phase of the research is to develop a roadmap and validate it with a number of organisations in different cultural contexts and leadership styles.
Originality/value
The authors argue that this is one of the most comprehensive systematic review on lean frameworks and roadmaps, ever produced in the literature to date.
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The brake controller is a key component of the locomotive brake system. It is essential to study its safety.
Abstract
Purpose
The brake controller is a key component of the locomotive brake system. It is essential to study its safety.
Design/methodology/approach
This paper summarizes and analyzes typical faults of the brake controller, and proposes four categories of faults: position sensor faults, microswitch faults, mechanical faults and communication faults. Suggestions and methods for improving the safety of the brake controller are also presented.
Findings
In this paper, a self-judgment and self-learning dynamic calibration method is proposed, which integrates the linear error of the sensor and the manufacturing and assembly errors of the brake controller to solve the output drift. This paper also proposes a logic for diagnosing and handling microswitch faults. Suggestions are proposed for other faults of brake controller.
Originality/value
The methods proposed in this paper can greatly improve the usability of the brake controller and reduce the failure rate.
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Tiziano Volpentesta, Esli Spahiu and Pietro De Giovanni
Digital transformation (DT) is a major challenge for incumbent organisations, as research on this phenomenon has revealed a high failure rate. Given this consideration, this paper…
Abstract
Purpose
Digital transformation (DT) is a major challenge for incumbent organisations, as research on this phenomenon has revealed a high failure rate. Given this consideration, this paper reviews the literature on DT in incumbent organisations to identify the main themes and research directions to be undertaken.
Design/methodology/approach
The authors adopt a systematic literature review (SLR) and computational literature review (CLR) employing a machine learning algorithm for topic modelling (LDA) to surface the themes discussed in 103 peer-reviewed studies published between 2010 and 2022 in a multidisciplinary article sample.
Findings
The authors identify and discuss the five main themes emerging from the studies, offering the state-of-the-art of DT in established firms' literature. The authors find that the most discussed topics revolve around the DT of healthcare, the process of renewal and change, the project management, the changes in value performances and capabilities and the consequences on the products of DT. Accordingly, the authors identify the topics overlooked by literature that future studies could tackle, which concern sustainability and contextualisation of the DT phenomenon.
Practical implications
The authors further propose managerial insights which equip managers with a revolutionary mindset that is not constraining but, rather, integration-seeking. DT is not only about technology (Tabrizi B et al., 2019). Successful DT initiatives require managerial capabilities that foster a sustainable departure from the current organising logic (Markus, 2004). This study pinpoints and prioritises the role that paradox-informed thinking can have to sustain an effective digital mindset (Eden et al., 2018) that allows for the building of momentum in DT initiatives and facilitates the renewal process. Indeed, managers lagging behind DT could shift from an “either-or” solutions mindset where one pole is preferred over the other (e.g. digital or physical) to embracing a “both-and-with” thinking balancing between poles (e.g. digital and physical) to successfully fuse the digital and the legacy (Lewis and Smith, 2022b; Smith, Lewis and Edmondson, 2022), enact the renewal, and build and maintain momentum for DTs. The outcomes of adopting a paradox mindset in managerial practice are enabling learning and creativity, fostering flexibility and resilience and, finally, unleashing human potential (Lewis and Smith, 2014).
Social implications
The authors propose insight that will equip managers with a mindset that will allow DT to fail less often than current reported rates, which failure may imply potential organisational collapse, financial bankrupt and social crisis.
Originality/value
The authors offer a multidisciplinary review of the DT complementing existing reviews due to the focus on the organisational context of established organisations. Moreover, the authors advance paradoxical thinking as a novel lens through which to study DT in incumbent organisations by proposing an array of potential research questions and new avenues for research. Finally, the authors offer insights for managers to help them thrive in DT by adopting a paradoxical mindset.
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Within the last two decades, entrepreneurship education has become institutionalized in Germany. It is offered as a stand-alone program or as part of a business degree, combining…
Abstract
Within the last two decades, entrepreneurship education has become institutionalized in Germany. It is offered as a stand-alone program or as part of a business degree, combining academic knowledge, practical skills, and personal development to enhance the entrepreneurial success of university graduates. While entrepreneurship education has experienced similar growth worldwide, its emergence in Germany is closely tied to the country’s political and economic developments. The significance of entrepreneurship education for a thriving entrepreneurial ecosystem and contemporary economic policy has been instrumental in advancing its academic recognition. This chapter provides a historical analysis of the academization of entrepreneurship in Germany. It explores the recursive and often idiosyncratic processes involving state and financial institutions, companies, and universities that have created, respecified, and mutually reinforced a subdiscipline and field of study. Academic entrepreneurship knowledge successively not only became relevant for starting a business but also for employment within the entrepreneurial infrastructure and beyond. This chapter follows a chronological order, highlighting three key stages in the academization of entrepreneurship education. First, the academic, financial, and political roots (I) of entrepreneurship up until the 1970s. Second, it explores the transformation (II) of entrepreneurship into a viable policy alternative and the challenges faced in establishing complementary research and education in higher education institutions during the 1980s. Finally, it sketches the institutionalization (III) of entrepreneurship as a central driver of government economic policy, allowing for the late bloom of entrepreneurship education and research at universities around the turn of the millennium.
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Noor Hidayah Shahidan, Ahmad Shaharudin Abdul Latiff and Sazali Abdul Wahab
The purpse of this study is to examine sustainable technology development (STD) during the “Valley of Death” phase encountered by university startups undertaking intellectual…
Abstract
Purpose
The purpse of this study is to examine sustainable technology development (STD) during the “Valley of Death” phase encountered by university startups undertaking intellectual property rights (IPR) commercialisation.
Design/methodology/approach
A comprehensive literature review was conducted after searching for relevant documents across multiple databases. Semi-structured interviews with university startup founders were also conducted as part of a qualitative case study.
Findings
This study resulted in two significant findings. First, the Valley of Death has been redefined in the specific context of IPR commercialisation by university startups. Second, the sustainable technology development framework (STDF) has been conceptualised to enhance the success rate of IPR commercialisation by university startups. The authors also identified three essential components of STD in the context of university startups: market development, technical efficiency and business sustainability.
Research limitations/implications
This exploratory research involved a thorough literature analysis. Given that only one qualitative case study was conducted, data saturation was not achieved. Further empirical research is needed to validate the conceptualised STDF.
Practical implications
The validated STDF will be a useful tool for enhancing the success of IPR commercialisation by university startups.
Originality/value
While others have focused on innovating business models, this study focused on an underexplored area: the sustainability of technology development during the commercialisation of IPR by university startups during the Valley of Death phase.
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